基于人口统计学的推荐算法的大数据实现

Li Wenzhe, Stanislav V. Grigorev
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引用次数: 0

摘要

利用搜索引擎的强大功能,通过关键词进行搜索,而只是被动地帮助人们搜索,这已经不足以满足人们更多的需求。推荐引擎,是能够主动发现用户过去、现在和未来的活动和需求规律,通过数据收集和分析来探索用户的爱好和兴趣,并主动将用户可能感兴趣的信息反馈给某一信息网络的用户,将用户可能感兴趣的内容推荐给该用户所需要的内容。采用基于用户、基于内容、基于人口统计的推荐机制思想,对这些真实数据进行分析计算,提取推荐结果推荐给用户,完成个性化的电影推荐。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Implementation of the Demographic-Based Recommendation Algorithm Using Big Data
Using the powerful functions of search engines, search through keywords, and only passively help people search, this has not been enough to meet more needs of people. Recommendation engines, is able to take the initiative to find the user in the past, present and future activities and demand rule, through data collection and analysis to explore the user's hobbies and interests, and active user may be interested in information feedback to the user of an information network, the user may be of interest to the content which needs to recommend to the user. The idea of user-based, content-based and demographic-based recommendation mechanism is adopted to analyze and calculate these real data and extract the recommendation results to recommend to users to complete personalized movie recommendation.
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